The team collected data on weight; heart rate; oxygen in the blood; skin temperature; activity, including sleep, steps, walking, biking and running; calories expended; acceleration; and even exposure to gamma rays and X-rays.

Altogether nearly two billion measurements including continuous data from each participant's wearable biosensor devices and periodic data from laboratory tests of their blood chemistry, gene expression and other measures were collected.

For example, in several participants, higher-than-normal readings for heart rate and skin temperature correlated with increased levels of C reactive protein in blood tests.

C reactive protein is an immune system marker for inflammation and often indicative of infection, autoimmune diseases, developing cardiovascular disease or even cancer.

Prof Snyder's own data revealed four separate bouts of illness and inflammation, including the Lyme disease infection and another that he was unaware of until he saw his sensor data and an increased level of C reactive protein.

The wearable devices could also help distinguish participants with insulin resistance, a precursor for Type 2 diabetes.

The study also revealed that declines in blood-oxygen levels during flights were correlated with fatigue but people recover quickly as oxygen rises they feel less tired.

Prof Topol added: "The desaturation of oxygen in flight was not something I anticipated,

"Whenever you walk up and down the aisle of a plane, everyone is sleeping, and I guess there may be another reason for that besides that they partied too hard the night before.

"That was really interesting, and I thought it was great that the authors did that."

Prof Snyder said: "We have more sensors on our cars than we have on human beings."

But in the future the situation will be reversed and people will have more sensors than cars do.

There is already millions of the devices out there including more than 50 million smart watches and 20 million other fitness monitors.

The professor added most monitors are used to track activity, but they could easily be adjusted to more directly track health measure.

With a precision health approach, every person could know his or her normal baseline for dozens of measures and any abnormality flagged up.